KR20190006560A - Method and system for satellite signal processing - Google Patents

Abstract

A method for tracking a plurality of signals from a single satellite comprises the steps of: receiving a first signal (s ₁ ) transmitted by a satellite (2); Receiving at least a second signal (s2) transmitted by the same satellite; Applying a pre-filtering process to determine accumulated in-phase and quadrature components of the first and second signals, and optionally any other signals; And applying a filtering process on the accumulated in-phase and quadrature components of the first and at least second signals to determine a range (r) and a range rate (v) of the satellites, And applying a filter. The method results in the determination of the range rate and range from a single satellite with an improved signal over the noise ratio.

Description

Method and system for satellite signal processing

The present invention relates to a method and system for tracking a plurality of signals from a single satellite and wherein the first and second signals transmitted by the same satellite are received and filtered to determine the range and range rate of the satellite.

Satellite navigation systems use a series of satellites at a Medium Earth orbit (MEO) location that provides geo-spatial positioning information. These satellites are generally at an altitude of 20,000 km with an orbital period of about 12 hours. Electronic receivers, commonly known as "sat-navs", use these satellites to establish their position up to a precision of a few meters, and use line-of-sight communications from satellites to receivers to determine longitude, latitude and altitude ≪ / RTI > The time signals also allow time synchronization to a high degree of accuracy by calculation of the current local time. A satellite navigation system with global coverage is commonly referred to as a global navigation satellite system, GNSS. There are two GNSSs as global motion GNSSs (as of 2013): systems in NAVSTAR (US GPS or global positioning system) and GLONASS (Russian system), China (Vader) and Europe (Galileo) And other local systems.

GNSS receivers use a plurality of signal tracking loops each dedicated to different signal types and / or satellites. Each signal transmitted by the satellite includes time information (time at which the signal is transmitted) and position information (position at which the signal is transmitted). In general, it is assumed that the filtered in-phase and quadrature components (90 ° or π / 2 out of phase) and the range of the satellite (distance between the satellite and the receiver) A signal having the time / position data used as a basis for determining the speed at which the mobile station is moving about is received.

However, signals received from the same satellite with the same range between the satellite and the receiver will arrive at different times by delay differences in processing within the receiver. For example, they may be due to various external factors such as passing through filters of different bandwidths, or ionospheric or tropospheric delay. The longevity delay is frequency dependent and influenced by both the elevation angle of the satellite (on the tangent plane of the local user) and the total electronic count along the signal path between the satellite and the receiver. The tropospheric delay includes components that depend on the transfer of signals through the dry atmosphere and less easily determined components that are subject to the transfer of signals through the wet atmosphere. Thus, solutions for eliminating the longevity delay component in signal processing for multiple signals from a single satellite have been proposed, for example, as in US 7,151,486 and operate on the basis of two carrier signals, whilst somewhat successful. There is also a problem of coherence delay in any pre-license delay estimation, which may be important. Alternative solutions include the use of a third carrier signal that allows for quick resolution of any carrier phase ambiguities, but they actually experience bad signal-to-noise ratios. The angle at which the signal is received will also partially determine errors by either a transfer of rights or a troposphere delay. The angle affects the distance in each medium traveled before the signal reaches the receiver, thus contributing to the amount of delay experienced by the signal.

In most situations, a single receiver will receive multiple signals of different types at any one point in time. A conventional receiver may be configured to generate a desired single type of signal (GPS L1 C / A signal) received from a plurality of satellites so as to be able to generate a single estimate for position, velocity and time (PVT) or position, And so on). Incorporating a large number of signals causes an increase in errors, among which errors due to the ionosphere and troposphere delay and noise to signal ratio will vary due to the relative positions (angle and distance) of the receiver and the satellite. Thus, each signal of interest will have its own inherent errors that may differ from all other signals of that type received from other satellites. The filtering techniques are used to reduce these errors when combining a plurality of identical types of signals, and the mathematical filtering function is applied to the combined signal and error data. For example, least squares filtering techniques are commonly used, and Kalman filters may also be used. The filtered data results in a signal estimate that is much more accurate than is otherwise available. These mathematical methods are also suitable for this type of filtering in the form of a single signal from a plurality of sources.

The removal of the component of the right of way also does not consider the use of the third carrier signal and the problem of circumstances in which the GNSS signal can be rejected, for example by jamming. Assuming that not all GNSS signals are interfered at the same time, these signals still require tracking. Along with the problem of signal-to-noise degradation, a fundamental problem of known techniques, this necessitates the ability to track multiple signals from a single satellite source, regardless of the environment.

The present invention aims to address these problems by providing a method of tracking a plurality of signals from a single satellite, the method comprising: receiving a first signal transmitted by a satellite; Receiving at least a second signal transmitted by the same satellite; Applying a pre-filtering process to determine accumulated in-phase and quadrature components of the first and at least second signals; And applying a filtering process to the accumulated in-phase and quadrature components of the first and at least second signals to determine the range and range rate of the satellite, the filtering process comprising applying a Kalman filter .

The output of the Kalman filter includes an estimate of the range for a single satellite and an estimate of the range-rate. Range and range rates can be used to generate a single estimate for PVT or PNT when extracted from the same way from a plurality of satellites (typically at least four are required). Thus, the method is advantageously repeated using a plurality of satellites.

The use of a Kalman filter to process a plurality of signals from a single satellite provides improved navigation capability because the signal-to-noise ratio of the range and range-rate estimates for the associated satellite is improved as a result of the operation of the Kalman filter . The result is that signals with larger signal-to-noise ratios can be used to compensate for signals having a lower signal-to-noise ratio received from the same satellite. The problem of signal jamming becomes less problematic due to this capability.

The first and at least the second signals may have different frequencies.

Preferably, the first and at least the second signals have the same frequency. In this situation, the first and at least the second signals may be transmitted at different times.

Preferably, the method is repeated using signals from a plurality of different satellites to generate a range and a range rate for each satellite, the location of the object including range and range rate estimates from a plurality of satellites ≪ / RTI > As described herein, estimates of range and range rates obtained from a single satellite are improved in accuracy by the Kalman filter process. Thus, an improved navigation fix can be obtained using this more accurate data. The method is preferably employed by each satellite used to provide the navigation position, but it still provides benefits when used by only one, or larger sub-set of satellites in use.

In another aspect, the present invention also provides a system for tracking a plurality of signals from a single satellite, the system comprising: a receiver for receiving a first signal transmitted by a satellite and at least a second signal transmitted by the same satellite An adapted receiver unit; And a pre-filtering process to determine cumulative in-phase and quadrature components of the first and at least second signals and a pre-filtering process to determine cumulative in-phase and quadrature components of the first and at least second signals, And a microprocessor adapted to apply a filtering process on the quadrature components, the filtering process comprising applying a Kalman filter.

The invention will now be described by way of example only and with reference to the accompanying drawings.

1 is a schematic diagram of a receiver and a satellite set up to function as part of a GNSS network within a first embodiment of the invention;
Figure 2 is a schematic diagram of a receiver unit used in the network of Figure 1;
3 is a schematic diagram of a satellite and a receiver unit set up to function as part of a GNSS network as part of a second embodiment of the present invention.

The present invention takes the approach of using a Kalman filter as the basis of a tracking architecture for a plurality of signals received by a receiver from the same satellite. By receiving the first signal transmitted by the satellite and receiving the second signal transmitted by the same satellite, the pre-filtering process can be applied to determine the accumulated in-phase and quadrature components of the first and second signals have. This then allows the filtering process to be applied to the accumulated in-phase and quadrature components of the first and second signals to determine the range and range rate of the satellite. The filtering process is a Kalman filter that provides a number of advantages when used with respect to signals from a single satellite, as described in more detail below.

Figure 1 shows a schematic diagram of a satellite and receiver unit set up to function as part of a GNSS network within a first embodiment of the invention. The network 1 comprises a satellite 2 (together with other satellites in the network not shown) and a receiver unit 3. The satellite 2 is in the orbit 4 above the surface of the earth 5 and the receiver unit 3 is located on the surface of the earth 5. The satellite 2 is positioned to be separated from the receiver unit 3 by a range r and the relative velocity between the satellite 2 and the receiver unit 3 is range-rate v. At time t ₁ , the satellite 2 transmits a first signal s ₁ having a frequency f ₁ to the receiver unit 3. At time t ₂ , the same satellite 2 transmits a second signal s ₂ , also having a frequency f ₁ , to the receiver unit 3.

Figure 2 is a schematic diagram of a receiver unit used in the network of Figure 1; The receiver unit 3 includes a receiver 6, a microprocessor 7 and a display output 8. The display output 8 may be integrated with the receiver unit 3 or connected directly or indirectly to the display (e.g., a liquid crystal display or other visual display) (e.g., With or without means, via a bus or other similar connected device). The first signal s ₁ and the second signal s ₂ are received at the receiver 6. The microprocessor 7 comprises pre-filtering means for first selecting the in-phase and quadrature components of the first signal s ₁ and the second signal s ₂ and for summing together the second similar components together , To form cumulative in-phase and quadrature outputs. Accumulated in-phase and quadrature satellite components are then provided to the filtering process to determine the range and range rate of the satellites 2. The filtering process involves using a Kalman filter.

The Kalman filter can be used to determine the physical laws of motion, known control inputs to the system, and a number of sequential measurements, such as, for example, It is a linear quadratic predictor using the dynamic model of the same system. The Kalman filter averages the prediction of the state of the system using weighted averages, so that the result of the weighted average calculation lies between the measured state and the estimated state, but is more accurate than itself by its estimated uncertainty. Because the new estimate and its covariance (used in the weighting system as an estimate of the uncertainty in the predicted state) are used in the next iteration, the process is a cyclic iterative process. The uncertainty of the measurements may be difficult to quantify, and therefore the performance of the filter is often discussed in terms of gain. Low Kalman gain emphasizes predictions, removes noise from the data, and high Kalman gain emphasizes measurements.

The Kalman filter model assumes that the real state of the system at time k evolves from the state at time k-1 according to equation 1:

Where F _k is the state transition model applied to the previous state at x _k-1

B _k is the control-input model applied to the control vector (u _k )

W _k is the noise based on the normal distribution of the covariance Q _k , w _k ~ N (0, Q _k )

At time _k , observation of z _k of the real state (x _k ) is done according to equation 2:

H _k is the observation model that maps the actual state space to the observed space and v _k is the observation noise assumed to be the zero mean Gaussian distribution by the covariance R _k , v _k ~ N (0, R _k ). At each step, the initial state and noise vectors are assumed to be independent.

If the Kalman filter is applied to the first signal component s ₁ and the second signal component s ₂ and the identified range and range rate, then they can determine the position of the receiver unit 3 by triangulating the signals from the various satellites And is supplied to an algorithm driven by the microprocessor 7 to be determined. This enables accurate determination of longitude, latitude and altitude. The Kalman filter approach can be used for a plurality of signals received from each single satellite used in the triangulation process, or for one or more depending on environmental conditions and / or signal strength.

The use of a Kalman filter to determine range and range rates and accordingly to track signals from a single satellite provides advantages. By combining the tracking of several satellite signals into a single tracking filter, stronger signals can be used to help track weaker signals. For example, re-acquisition of signals subsequent to signaling stops may be faster if the particular frequency signal is blocked or if a particular satellite is unavailable, because range and range-rate estimates are maintained by tracking the remaining signals . In the estimates presented in the measurement generation algorithm that determine the position of the receiving unit 2, noise is also reduced because more signals are used, resulting in more accurate navigation solutions. In addition, models of ionospheric and atmospheric delays are maintained by a filter with a correlation time of several minutes or more, and again sufficient to maintain performance even by significant signal outage.

Variations in signal strength may result in slow fading effects (e.g., multipath signals and signal obscuration by objects such as buildings in fixed site operation) or fast fading effects Multi-path signal problems). If the variations are fast, for example, at frequencies greater than 10 -20 Hz, the Kalman filtering method may be used to reject such variations in position determination. When one or both signals are interrupted, intentionally or unintentionally, the method of the present invention compensates for loss of signal by using any other remaining frequency signals transmitted by the satellite to maintain the tracking filter performance .

In one alternative embodiment of the present invention, the Kalman filter of this aspect is further analyzed. 3 shows a schematic diagram of a receiver and a satellite set up to function as part of a GNSS network as part of a second embodiment of the present invention. The network 9 includes a satellite 10 (having other satellites in the network not shown) and a receiver unit 11. The satellite 10 is in the orbit 12 on the surface of the earth 13 and the receiver unit 11 is located on the surface of the earth 13. The satellite 10 is positioned to be separated from the receiver unit 11 by the range r and the relative velocity between the satellite 10 and the receiver unit 11 is range-rate v. At time t ₁ , the satellite 10 transmits a first signal s ₁ having a frequency f ₁ to the receiver unit 11. At time t ₁ , the same satellite 10 also transmits a second signal s ₂ with a frequency f ₂ to the receiver unit 11, where f ₁ ≠ f ₂ . As described above with reference to Fig. 2, the receiver unit 11 includes a receiver 6, a microprocessor 7, and a display output unit 8. The display output 8 may be integrated into the receiver unit 11 (e.g., a liquid crystal display or other visual display) or connected directly or indirectly to the display (e.g., to other hardware or processing means connected therebetween) Via a bus or other similar connection device, without any other hardware or processing means connected thereto by or in between). The first signal s ₁ and the second signal s ₂ are received at the receiver 6. The microprocessor 7 comprises pre-filtering means for first selecting the in-phase and quadrature components of the first signal s ₁ and the second signal s ₂ and for summing together the second similar components together , And forms cumulative in-phase and quadrature outputs. The accumulated in-phase and quadrature components are then provided to the filtering process to determine the range and range rate of the satellites 2. Also as described above, the filtering process involves using a Kalman filter.

Other embodiments falling within the scope of the claims will be apparent to those skilled in the art. For example, the receiver unit 3, 11 may be a stationary (stationary site operation), a movement (movement operation), a standalone unit, Devices. ≪ / RTI >

Claims (6)

A method for tracking a plurality of signals from a single satellite,
Receiving a first signal transmitted by a satellite;
Receiving at least a second signal transmitted by the same satellite;
Applying a pre-filtering process to determine accumulated in-phase and quadrature components of the first and at least second signals; And
Applying a filtering process to the accumulated in-phase and quadrature components of the first and at least second signals to determine a range and a range rate of the satellite,
Wherein the filtering process comprises applying a Kalman filter. The method according to claim 1,
Wherein the first and at least second signals have different frequencies. The method according to claim 1,
Wherein the first and at least second signals have the same frequencies. The method of claim 3,
Wherein the first and at least second signals are transmitted at different times. 5. The method according to any one of claims 1 to 4,
The method is repeated using signals from a plurality of different satellites to generate a range and a range rate for each satellite and the position of the object is computed using the range and range rates thus generated, Lt; / RTI > A system for tracking a plurality of signals from a single satellite,
A receiver unit adapted to receive a first signal transmitted by a satellite and at least a second signal transmitted by the same satellite; And
A pre-filtering process to determine cumulative in-phase and quadrature components of the first and at least second signals and a pre-filtering process to determine the range and range rate of the satellite, And a microprocessor adapted to apply a filtering process to the phase and quadrature components,
Wherein the filtering process comprises applying a Kalman filter.

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